Dismantling the Quantitative–Qualitative Divide: Comments on Hypothesis Testing, Induction, Statistics, Fiction and Epistemological Anarchy
The conventional quantitative-qualitative divide in management research mixes up several very different dimensions. We analyze two of these dimensions – statistical versus non-statistical, and hypothesis testing versus induction – and see how they fit some examples of published management research. This leads to the conclusion that the conventional divide omits many potentially useful possibilities, such as non-statistical hypothesis testing and statistical induction. If the analysis were to be extended to other dimensions (e.g. subjectivist versus objectivist), there would be many more excluded types of research.
We also argue that the implicit assumption that each of the two dimensions cover all possibilities is wrong: the first dimension can be extended to include deterministic laws, assertions of possibilities, and the consideration of fictional scenarios; and the second to include deductive (as opposed to hypothetico-deductive) research, and “normal science” research based on questions defined by an established paradigm. This reinforces the conclusions that the conventional perspective is likely to seriously impoverish research by ruling out many interesting possibilities, and that placing too much reliance on any scheme for categorizing research may be unhelpful.
Keywords: Quantitative Research, Qualitative Research, Hypothesis testing, Statistics, Fiction
Dr Michael Wood
Portsmouth Business School
Affiliation not supplied